evidence_for

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does disclose useful output behavior—separating evidence_note from stance and passing disclaimers through—but it does not explicitly state read-only semantics, prerequisites, or error behavior. This is adequate but not fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three dense, purposeful sentences: purpose, usage trigger, parameter semantics, and output handling. Every sentence earns its place and there is no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has four parameters and an output schema, the description covers the core invocation context, parameter semantics, and key output distinctions. It lacks explicit sibling routing and operational caveats, but nothing essential for calling the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, and the description adds real value on top: it clarifies that from and to are concept names, gives example relation values like causes/enables/requires, and explains as_of for past-as-of queries. This goes beyond the bare schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a concrete action and object: confirming the evidence for one causal link ('A 가 B 를 유발한다'는 한 연결의 근거를 확인한다). It also states the tool is for validating causality in a previous answer, which separates it from sibling tools like path_between or enumerate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'앞선 답에 쓰인 인과를 검증할 때 쓴다' provides a clear trigger condition for when to use the tool. It does not explicitly name alternative tools or state when not to use it, but the intended context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.